MétaCan
Menu
Back to cohort
Record W4392954874 · doi:10.2514/1.a35873

Addressing the Orbital Debris Threat Directionality for Enhanced Protection of Low-Earth-Orbit Robotic Spacecraft

2024· article· en· W4392954874 on OpenAlexafffundabout
Victor O. Babarinde, Patrick Domingo, Igor Telichev

Bibliographic record

VenueJournal of Spacecraft and Rockets · 2024
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpacecraftAerospace engineeringSpace debrisLow earth orbitAstrobiologyGeocentric orbitDebrisOrbit (dynamics)AeronauticsOrbital maneuverMedium Earth orbitDirectionalityComputer scienceEnvironmental scienceEngineeringPhysicsSatelliteMeteorology

Abstract

fetched live from OpenAlex

This study conducts a detailed investigation into addressing the directionality of micrometeoroid and orbital debris (MMOD) threats, emphasizing the strategic placement of protective resources on a spacecraft. The research considers the conversion of the structural sandwich panel and the multilayer thermal blanket into multifunctional elements that provide MMOD protection without causing substantial weight gain or affecting operational parameters. The effectiveness of the reconfigured components, such as the foam core sandwich panel and multilayer insulation blanket toughened by Nextel fabrics, is evaluated using developed and validated numerical models and experimental methods. Their performance is demonstrated by meeting the protection needs of the Canadian robotic Radarsat Constellation Mission spacecraft.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.261
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Spacecraft and RocketsSame topicSpace Satellite Systems and ControlFrench-language works237,207